When we have to witness a failure of maintenance in an important company for the operation, then it is possible to ask itself: how a company of the best evaluated in his rubro can avoid failures of this nature? Undoubtedly, the answer is focused on improving the maintenance management of infrastructure and equipment.

The maintenance classes can be summarized in three: corrective, preventive and predictive.

The first is the one that the organization had to resort to in this last failure, and consists of correcting or repairing the system when the failure has already occurred. Unfortunately, when you have to resort to this type of maintenance on infrastructure and equipment that is critical, not only have the consequences that we all know in the case of Metro, but also, there are higher repair costs and economic losses due to service stoppage. . Therefore, it is easy to imagine that neither Metro nor any other company expects to maintain this form.
Therefore, the idea is not to reach this type of maintenance, but to do preventive maintenance, or even a step further, to do predictive maintenance, which is possible today thanks to the new technologies present in the market.
Benefits of preventive and predictive maintenance
Preventive maintenance is a set of techniques that aims to reduce and / or avoid equipment failures to ensure their full availability and performance at the lowest possible cost. To carry out this practice, periodic inspection routines are required, as well as monitoring of operational conditions and monitoring of usage information or operating times. It is characterized by executing a maintenance task due to the occurrence of a known condition to avoid a known failure.

On the other hand, predictive maintenance is much more advanced and with greater benefits. It is aimed at the critical components of the system. This type of maintenance is based on the analysis of millions of data of different condition or operation variables of the equipment, data that are current and historical, and that through mathematical models allow predicting that there is a probability that a fault occurs in a period of future time given. This results in greater reliability and availability of the equipment.

This type of maintenance program reports a great cost saving since in addition to detecting faults early enough, it allows to schedule the repair time and supplies and labor that the task will require well in advance.

Today Big Data technologies – analysis of large volumes of data in real time – and mobility, allow the people in charge of maintenance to discover patterns and new conditions that will produce a failure in the future. Mobility, meanwhile, allows to inform critical agents in a timely manner or even take preventive measures directly from mobile devices.

The Big Data technologies of today allow to do predictive analysis, and this has a good opportunity for improvement in maintenance management.

With the use of Big Data what we want is to have to resort as little as possible to corrective maintenance (it is carried out when the machine is broken or has suffered a failure) therefore the analysis will focus on obtaining data to be able to do a preventive or predictive maintenance. These two types of maintenance have as main advantage that it is not necessary to cut the production process to fix the machinery because they are a set of techniques that aims to reduce system failures and thus anticipate them.

Maintaining the system manually takes time and is more expensive, because to carry out these maintenance methods it is very important to have a constant analysis of both machines and systems, at the same time of a thorough surveillance, so that the use of a CMMS facilitates work, reduces costs and the time necessary to carry out said activity.

Therefore, the use of Big Data for maintenance management offers us a wide range of possibilities for improvement in the development of this activity, since we obtain more precise and detailed information of each of our elements, it facilitates the assignment of tasks for the maintenance personnel, and it offers us detailed information of each element that will facilitate the work to the maintenance managers at the time of repairing faults.

And now we invite you to reflect knowing the advantages and the large number of benefits that can be obtained using Big Data in maintenance management, if you still think that using a CMMS for the maintenance management of your equipment is not really useful.

The use of predictive maintenance is to establish, in the first place a historical perspective of the relationship between the selected variable (temperature, vibration, etc …) and the life of the component.

This is achieved by taking readings of data, for example the vibration of a bearing, at periodic intervals until the component breaks or breaks down, collecting and analyzing the reading of the data obtained. According to the study of said data, must determine if it compensates or does not apply the predictive maintenance strategy, taking into account different variables; as the cost of the element to replace, the repair time during which the machinery has to be stopped and with it the production, the cost that will involve the collection of information and its treatment, etc.

The first step is to determine the variables physical to monitor that are indicative of the condition of the machine. As can be deduced, this decision is essential and determinant when it comes to obtaining a satisfactory result in maintenance.

The purpose of the data monitoring is to obtain an indication of the mechanical condition or health status of the machine, so that can be operated and maintained safely and effectively. According to the objectives to be achieved with the monitoring of the condition of a machine must be distinguished between surveillance, protection and diagnosis. Vigilance: Its purpose is to indicate when there is a problem.

It must distinguish between good and bad condition, and if it is bad to indicate its degree of severity.Protection of machines: Its objective is to avoid catastrophic failures. A machine is protected, if when the values ​​that indicate its condition reach values ​​considered dangerous, the machine stops automatically.

Diagnosis of faults: Its objective is to define what the specific problem is and estimate how much longer the machine can operate without risk of suffer a breakdown. I bet on predictive maintenance because we consider that it has some very important advantages with respect to the other two mentioned.

PREDICTIVE MAINTENANCE WITH BIG DATA An opportunity for management

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